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An Efficient, Platform-Independent Map Rendering Framework for Mobile Augmented Reality.

Authors :
Huang, Kejia
Wang, Chenliang
Wang, Shaohua
Liu, Runying
Chen, Guoxiong
Li, Xianglong
Source :
ISPRS International Journal of Geo-Information. Sep2021, Vol. 10 Issue 9, p593. 1p.
Publication Year :
2021

Abstract

With the extensive application of big spatial data and the emergence of spatial computing, augmented reality (AR) map rendering has attracted significant attention. A common issue in existing solutions is that AR-GIS systems rely on different platform-specific graphics libraries on different operating systems, and rendering implementations can vary across various platforms. This causes performance degradation and rendering styles that are not consistent across environments. However, high-performance rendering consistency across devices is critical in AR-GIS, especially for edge collaborative computing. In this paper, we present a high-performance, platform-independent AR-GIS rendering engine; the augmented reality universal graphics library (AUGL) engine. A unified cross-platform interface is proposed to preserve AR-GIS rendering style consistency across platforms. High-performance AR-GIS map symbol drawing models are defined and implemented based on a unified algorithm interface. We also develop a pre-caching strategy, optimized spatial-index querying, and a GPU-accelerated vector drawing algorithm that minimizes IO latency throughout the rendering process. Comparisons to existing AR-GIS visualization engines indicate that the performance of the AUGL engine is two times higher than that of the AR-GIS rendering engine on the Android, iOS, and Vuforia platforms. The drawing efficiency for vector polygons is improved significantly. The rendering performance is more than three times better than the average performances of existing Android and iOS systems. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
22209964
Volume :
10
Issue :
9
Database :
Academic Search Index
Journal :
ISPRS International Journal of Geo-Information
Publication Type :
Academic Journal
Accession number :
152742411
Full Text :
https://doi.org/10.3390/ijgi10090593